Trading Costs of Asset Pricing Anomalies Andrea

Transcript:Trading Costs of Asset Pricing Anomalies Andrea:
Trading Costs of Asset Pricing Anomalies Andrea Frazzini AQR Capital Management Ronen Israel AQR Capital Management Tobias J. Moskowitz University of Chicago and NBER Copyright 2012 © by Andrea Frazzini, Ronen Israel, and Tobias J. Moskowitz. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of AQR Capital Management, LLC its affiliates, or its employees. The information set forth herein has been obtained or derived from sources believed by author to be reliable. However, the author does not make any representation or warranty, express or implied, as to the information’s accuracy or completeness, nor does the author recommend that the attached information serve as the basis of any investment decision. This document is intended exclusively for the use of the person to whom it has been delivered by the author, and it is not to be reproduced or redistributed to any other person. This presentation is strictly for educational purposes only. Motivation Cross-section of expected returns typically analyzed gross of transactions costs Questions regarding market efficiency should be net of transactions costs Are profits within trading cost bounds? Measure of limits to arbitrage? Research Questions: How large are trading costs faced by large arbitrageurs? How robust are anomalies in the literature after realistic trading costs? At what size do trading costs start to constrain arbitrage capital? What happens if we take transactions costs into account ex ante? How does the tradeoff between expected returns and trading costs vary across anomalies? Trading Costs of Asset Pricing Anomalies - Frazzini, Israel, and Moskowitz 2 Objectives Measure trading costs of an “arbitrageur” Quantify limits to arbitrage Understand the cross-section of net returns on anomalies Model of trading costs for descriptive and prescriptive purposes Construct optimized portfolios 3 Trading Costs of Asset Pricing Anomalies - Frazzini, Israel, and Moskowitz What We Do Take all (longer-term) equity orders and executions from AQR Capital 1998 to 2011, $721 billion worth of trades, traded using automated algorithms Data just updated through September 2013 > $1.1 trillion worth of trades U.S. (NYSE and NASDAQ) and 18 international markets— *Exclude “high frequency” (intra-day) trades Use actual trade sizes and prices as well intended trade sizes and prices to calculate Price impact and implementation shortfall (e.g., Perold (1988)), which includes “opportunity cost” of not trading More accurate picture of real-world transactions costs and tradeoffs Get vastly different measures than those in